Send to

Choose Destination
See comment in PubMed Commons below
IEEE Trans Pattern Anal Mach Intell. 2006 Sep;28(9):1501-12.

A new convexity measure based on a probabilistic interpretation of images.

Author information

Machine Vision Group, Department of Electrical and Information Engineering, PO Box 4500, 90014, University of Oulu, Finland.


In this paper, we present a novel convexity measure for object shape analysis. The proposed method is based on the idea of generating pairs of points from a set and measuring the probability that a point dividing the corresponding line segments belongs to the same set. The measure is directly applicable to image functions representing shapes and also to gray-scale images which approximate image binarizations. The approach introduced gives rise to a variety of convexity measures which make it possible to obtain more information about the object shape. The proposed measure turns out to be easy to implement using the Fast Fourier Transform and we will consider this in detail. Finally, we illustrate the behavior of our measure in different situations and compare it to other similar ones.

[Indexed for MEDLINE]
PubMed Commons home

PubMed Commons

How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for IEEE Engineering in Medicine and Biology Society
    Loading ...
    Support Center